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remiehneppo

Code Generator MCP Server

by remiehneppo

Code Generator MCP Template Server

An MCP (Model Context Protocol) server built using Python's FastMCP framework. It exposes 4 precise, structured code-generation tools backed by prompt templates to generate production-grade, parsed code using local or cloud-based OpenAI-compatible APIs (such as llama-server, qwen-coder, gemma-12b, or OpenAI's API).

๐Ÿš€ Features

Exposes 4 key MCP tools that use structured templates to instruct the model to think step-by-step and produce clean, executable code:

  1. generate_standard_function (Template 1): Generates a standalone function based on constraints, edge cases, test cases, and external integration notes.

  2. generate_codebase_context (Template 2): Generates a function that respects and integrates with existing codebase structures and dependencies.

  3. generate_bugfix_refactor (Template 3): Focuses on refactoring or repairing current buggy implementations based on problem descriptions and test expectations.

  4. generate_multi_function_module (Template 4): Generates a multi-function module, validating that there are no circular dependencies or undefined functions.

โš™๏ธ Parser & Guardrails

  • Markdown Stripper: Automatic code parsing (extract_code_from_response) strips any markdown code blocks (```python) generated by instruct models, guaranteeing only raw executable code is returned.

  • Reasoning Fallback: Correctly handles DeepSeek-style reasoning models or llama-server configurations where all output is redirected into the reasoning_content field instead of content.

  • Max Tokens Guardrail: Enforces a 2048 token limit per request to prevent local model reasoning loops and timeouts.


Related MCP server: apcore-mcp

๐Ÿ› ๏ธ Configuration

Configure the server using command-line arguments or environment variables:

Setting

CLI Argument

Environment Variable

Default Value

Description

API URL

--api-url

CODE_GEN_API_URL / OPENAI_BASE_URL

https://api.openai.com/v1

OpenAI-compatible endpoint

Model

--model

CODE_GEN_MODEL / OPENAI_MODEL

gpt-4o

The model name to target

API Key

--api-key

CODE_GEN_API_KEY / OPENAI_API_KEY

(Empty)

API token (optional for local endpoints)

WARNING

For security reasons, do not pass--api-key via command-line arguments as it will be visible in plain text in the host process table. Use the environment variables instead.


๐Ÿ’ป Getting Started

Prerequisites

  • Python 3.10+

  • Dependencies installed in virtual environment:

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Running Locally

To run the MCP server directly over standard input/output (stdio):

python src/code_generator_mcp/server.py --api-url http://localhost:8008/v1 --model gemma-12b

Testing during development

You can use mcp dev (from MCP CLI) to test the server interactively in a development UI:

mcp dev src/code_generator_mcp/server.py -- --api-url http://localhost:8008/v1 --model gemma-12b

๐Ÿ”Œ Integration Setup

To use this server with your favorite MCP client (like Claude Desktop or Cursor):

Claude Desktop Configuration

Open your Claude Desktop config file (usually located at ~/.config/Claude/claude_desktop_config.json on Linux/macOS or %APPDATA%\Claude\claude_desktop_config.json on Windows) and add the following entry:

{
  "mcpServers": {
    "code-generator-mcp": {
      "command": "/path/to/project/.venv/bin/python",
      "args": [
        "/path/to/project/src/code_generator_mcp/server.py"
      ],
      "env": {
        "CODE_GEN_API_URL": "http://localhost:8008/v1",
        "CODE_GEN_MODEL": "gemma-12b"
      }
    }
  }
}

๐Ÿงช Testing

The codebase includes a fully-featured unit and integration test suite using pytest. Run tests with:

.venv/bin/pytest
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Maintenance

โ€“Maintainers
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โ€“Releases (12mo)
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